The sign-language can be used as a communication means between avatars having no common language. As a trial to overcome the linguistic barrier, we have previously developed a 2D model-based sign-language chatting system between Korean and Japanese on the the Internet. In that system, there have been some problems to be solved for natural animation and real-time transmission. In this paper, we employ a 3D character model for stereoscopic gestures in the sign-language animation. We also utilize CG animation techniques which use the variable number of frames and a cubic spline interpolation in order to generate realistic gestures. For real-time communication, on the other hand, we make use of an intelligent communication method on a client-server architecture. We implement a preliminary communication system with Visual C++ 5.0 and Open Inventor on Windows platforms. Experimental results show a possibility that the system could be used for avatar communications between different languages.

We propose a class-incremental learning framework for human activity recognition based on the Bag-of-Sequencelets model (BoS). The framework updates learned models efficiently without having to relearn them when training data of new classes are added. In this framework, all types of features including hand-crafted features and Convolutional Neural Networks (CNNs) based features and combinations of those features can be used as features for videos. Compared with the original BoS, the new framework can reduce the learning time greatly with little loss of classification accuracy.

This Letter proposes a timer based ordered registration (TBOR) scheme for CDMA private user zone (PUZ) service. The proposed TBOR scheme solves the problem that both the PUZ system loads and the public system loads are increased due to excessive registration. Also the TBOR scheme is quite simple to implement and compatible with the existing public CDMA system.